Modern motor vehicles are equipped with a plurality of sensors for detecting objects in the surroundings of the particular vehicle. The pieces of information gathered this way are used for controlling a plurality of assistance systems, which may assist the vehicle driver and may optionally automatically intervene in the driving process. A particularly reliable ascertainment of the vehicle surroundings is required for systems which are partially automated and, primarily, highly automated, and for autonomously driving systems. These pieces of information regarding the surroundings are then used as the basis for making decisions, such as, for example, whether a lane change may take place. In order to provide for a highly reliable ascertainment of the vehicle surroundings, multiple sensors and/or sensor technologies, such as, for example, radar, LIDAR, video or the like, are installed on the vehicle in such a way that a preferably complete 360° all-around visibility is achieved. The different sensor technologies have specific advantages and disadvantages in this case. For example, some of the surroundings sensors utilized in the vehicle nowadays, such as, for example, LIDAR or radar sensors, only have a horizontal viewing area. With the aid of radar sensors, it may be detected, for example, that an object is located in the driving area. The object cannot be classified with sufficient probability as a bridge, however, in particular at a far distance. Even if the object is detected as a bridge, it is not possible, due to the insufficient separability in the angle of elevation, to decide whether a further stationary object is located under the bridge. A detection is also nearly impossible even with the aid of horizontally oriented LIDAR sensors or laser scanners, due to the limited vertical field-of-view. On the other hand, it is not possible to reliably detect a bridge and whether it is unobstructed with the aid of video sensors, due to the insufficient resolution. This applies, in particular, when visibility is poor.
Due to the absence of a vertical viewing area and due to the limited capability to separate based on elevation, these sensors are not capable of directly measuring the underpassability of a bridge. The sensors available nowadays have functional deficiencies in the cases, in particular, in which a stationary vehicle blocks the passage.
In order to prevent the situation in which braking is carried out whenever a static object near the road is encountered, such as, e.g., a bridge or a tunnel entrance, the braking in current driver assistance systems in response to an immobile object may be postponed until the object has been reliably detected as an obstacle. This strategy is not a viable solution for highly automated systems, however.
Given that sensors and sensor sets currently available in the automotive sector have a limited capability to separate based on elevation, the sufficient detection of the underpassability and through-passability of bridges and tunnel entrances is a fundamental problem.